Currently, many studies of brain heron systems activity employ multineuron activity recording techniques. To this end computers with large memory capacity are based, but even this fails to provide the required efficiency of detecting rapidly varying signals with multiplicity of diverse waveforms.
Known in the art is a data compressor (SU,A,1101832), comprising an analog-to-digital converter with the input thereof constituting the compressor input, a data processor with the data inputs thereof connected to the analog-to-digital converter output via a data bus and with the outputs thereof constituting the compressor outputs, and a controller with the control input thereof interconnected with the control input of the data processor and connected to the control output of the analog-to-digital converter, with the other input thereof connected to another outputs of the data processor, with the control output thereof connected to yet another control input of the data processor and with the address output thereof connected via the address bus to the address input of the data processor.
This known in the art data compressor compares each current sample of the signal to the preceeding sample and therefore, if a sample is repeated, it is recognized as a new signal, i.e. the compressor passes a signal even if it repeats the waveform of the preceeding signal. This significantly reduces compression efficiency when solving problems of detecting interrelations between rapidly varying signals of diverse waveforms, if the number of possible waveforms is rather small.